Ne w t re n d s i n s o c i a l co mmerce: just a hy pe or a source of
s u s t a i nable advantage?
University of Applied Science Northwestern Switzerland, Switzerland
This paper describes the new trends in social commerce within B2C e-commerce. The main objective is
to ﬁgure out if these new trends are just a hype or if it will change the e-commerce sustainable. There
were 4 new trends selected within this paper which will be analysed on a detailed level. There exists
some more trends within social commerce, but the selected trends are the most promising ones.
Keywords: augmented reality, B2C , community marketing, consumer generated data, CRM, e-
commerce, hype, new trends, social commerce, social graph, social marketing, social networks
The trend social commerce isn‘t new at all. Since a few months, reviews and ratings of products and services are
established and will be already used to generate customer behaviour patterns (Singh 2009) and generate consumer
speciﬁc recommendations. The new trends in social commerce will be a deeper integration of consumer generated
data (Gartner 2009), social graph (Lang 2010), augmented reality (Lang 2010) and community marketing (Gartner
2009) to mention only the most interesting ones. This paper focus on these most promising new trends. Accord-
ing the literature they are also the most frequently mentioned ones.
2. Social commerce
Social commerce can be deﬁned like „Social commerce: Selling with social media - the use of social media in the
context of e-commerce.“ (Socialcommercetoday, 2010).
The trend with social commerce started as diﬀerent e-commerce companies gave their customers possibilities to
rate and comment the oﬀered products. These new features provides the customers the functionality either to
rate the products they bought or they can make their decision to buy a product based on these informations. To-
day this recommender systems are the basis for today social commerce applications like shown below.
Source: Amazon (2010)
The „Hype Cycle for E-Commerce“ of Gartner (2009) in the following graphical illustration shows also a lot of
future social topics within e-commerce.
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Source: Gartner (2010)
2.1. C o n s u m e r g e n e r a t e d d a t a
In a study of the Organisation for Economic Co-operation and Development, OECD (2007), consumer generated
data is described as „empower the user to contribute to developing, rating, collaborating on and distributing
Internet content and customising Internet applications“. Gartner (2009) assumes that the consumer generated
data hype is adolescent and will have a market penetration of 20% to 50% of the target audience.
Today the consumer generated data like audio and video data is mostly used for the self-expression of a person. In
the future such data can be used within e-commerce to extend the recommender system. In a study from Fittkau
& Maaß (2008) they showed by surveys that 46,5% take the ratings of other users in consideration before they buy
a product or service.
Source: solcomhouse (2010)
One of the biggest problems in consumer generated audio and video data are the legal aspects, especially with
copyright issues. According to Goldstone and Gill (2008) the situation about the responsibilities and the judgment
is still unclear. Goldstone and Gill (2008) also mentioned that diﬀerent media companies have entered into con-
tent licenses with YouTube which include to share advertisement revenues. Such deals are currently increasing.
2.2. S o c i a l g r a p h
According the study of Lang (2010) the social graphs have a good chance in the future. As shown in the study of
Fittkau & Maaß (2008) the purchasing behaviour has a dependency to the ratings of other users. With the social
graph an e-commerce store has the possibility to link a social network (like Facebook, Xing and others) with the
ratings. The outcome is that the user can see who from his social environment has bought which product and
what was the rating of it. The following illustration shows the relationship in a social environment.
Source: Google (2010)
The survey within the study of Fittkau & Maaß (2008) showed that 65,9% says that the truth of the rating can‘t
be proven and 45% thinks that this content also may be intentional manipulated. As Lang (2010) mentioned in his
study the relevance of ratings from the own social environment is higher which leads to a higher chance that a
product will be bought if a friend recommended it.
2.3. A u g m e n t e d r e a l i t y
The augmented reality allows to turn the e-commerce in a special shopping experience. The technology which is
used within the augmented reality allows for example to create a virtual dressing room (Evsan 2010) or creating
more fun while shopping (Elliott 2009). According to Lang (2010) also a relation between the augmented reality
and location based services could be build up. As today a lot of mobile phones contain a GPS (global positioning
system) receiver and a camera, this technologies could be linked and if a user is in a unknown city he could take a
picture and the combination of both technologies could tell him where he is and what is near to him. There exists
already such applications for the mobile phones (like Layar, shown in the picture below).
Source: Layar (2010)
Also in the study of Gartner (2009) this topic will be addressed under the title „Rich Information Visualization“.
Gartner (2009) rates this trend as an Emerging trend with a high beneﬁt for the supplier.
2.4. C o m m u n i t y m a r k e t i n g
The community marketing is a possibility to focus the marketing strategy to a special community. Within the
study from Gartner (2009) this community marketing can be used in the following ways: „company-sponsored
public communities (anyone can join) or private communities (invited or registered users only)“. Also Kaeppeli
(2010) refers in his presentation about e-commerce trends to such communities like buying groups and user gen-
erated cross selling. In contrast to the social graph, the community marketing focus on a whole community which
is interested in the same product or service, whereas the social graph focus more on the personal relationships
between the users.
The community marketing is a combination of the explained trends social graph and consumer generated data. In
combination with the data from these two other trends the community marketing can be made highly eﬀective
and address a lot of users of an e-commerce solution. In a study from eMarketer (2008) they ﬁgured out, that 61%
of the surveyed students asks their friends to know more about a product and still 38% look at others using it.
Within e-commerce much more changes in technologies and new trends will occur in the future. The trends I
described more in details seems to be the ones who will get used in e-commerce very soon. The social graphs are
already used in some way, but not as deep as described in this paper. Regarding the research I think that the
trends social graph and the augmented reality will be used more in the future. The reason for this conclusion is,
that both technologies are already used in a small part of the e-commerce world (Elliott 2009 and Evsan 2010) and
this trends fulﬁl the wish of the users to be part of the community (social graph) and to get the same shopping
experience as they visit a store physically (augmented reality).
As the personal feelings and the opinion of the own personal environment is more important than the one of a
whole „unknown“ community, I don‘t think that the community marketing will have a big growth in the future. I
assume that the consumer generated data will rest reduced to ratings and opinions to products and services.
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